需求分析→系统设计→代码执行→质量审计→交付验收，一键完成大型项目全自动开发。 Requirements Analysis → System Design → Code Execution → Quality Audit → Delivery Acceptance. One command to autonomously develop large-scale projects.
A kickoff protocol (agent skill) for multi-step tasks. Before writing any code, the agent must: run a spec interview, batch every human-authorization step into one checklist, build a self-verification loop (log sink + verify script + dry-run) *before* the feature itself, and build comparable variants instead of blocking on third-party decisions.
Sixteen guidance modules and one assembler on top of the free Toutour skill: two-tier tours, action-gated steps, event-driven checklists, ambient nudges, commerce patterns, a GA4 funnel adapter, and a parameterized Playwright harness. 106 end-to-end checks included.
This skill is based on practical Power Platform delivery patterns for safely creating, reviewing, and modifying Power Automate cloud-flow JSON in Dataverse solution exports. It focuses on issues that often break real client automations: runAfter paths, renamed action references, connection references, hardcoded values, TRY/CATCH logging, import safety, validation, and rollback notes.
利用者との対話を通じて依頼内容を整理し、用途に合うAIサービスの候補と、利用者が確認・編集できるプロンプト案を作成します。 Helps users clarify their task through conversation, suggests AI service options, and creates a prompt draft that users can review and edit.
Connect any MCP-compatible AI agent (Claude, Cursor, Copilot, Codex, Windsurf, Amp, Cline) to Penpot to create, audit, and maintain design systems — tokens, flows, interactions, animations, and design-to-code export to HTML/CSS/React.
Turn prompts or workflows into testable, launch-ready AI Skill products.